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Center for Nonlinear Studies |
Electric Vehicle holds promise to improve the energy efficiency and environmental impacts of transportation. However, widespread use of EVs can impose significant on electricity-distribution systems due to their added charging loads. A centralized EV charging schedule model is proposed, which coordinates the charging of EVs that have flexibility. The model uses stochastic program technique. It captures the uses of distributed energy resources, uncertainties around EV arrival times and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. A Monte Carlo-based sample-average approximation technique is proposed. A sequential sampling approach is applied to dynamically determine the optimal size of the sampled generated scenario tree to give a solution with desired quality at minimal computational cost.
Host: Chris Neale